Design novel dual agonists for treating type-2 diabetes by targeting peroxisome proliferator-activated receptors with core hopping approach

Predicting the bioactive compounds of Lentinula edodes and elucidating its interaction with genes associated to obesity through network pharmacology and in-vitro cell-based assay

Mushrooms are traditionally used for various medicinal purposes in traditional oriental medicine. The Japanese and Chinese are familiar with the medicinal macro fungus Lentinula edodes (Shiitake mushroom). This study aims to evaluate the role of chemical compounds from L. edodes using network pharmacology and in-vitro studies for management of Obesity. Bioactive compounds in extracts of L. edodes were identified by GC-MS analysis. Compounds were later screened for their drug-like property by Lipinski's rule. In addition, public databases (SEA, STP, Omim and DisGenet) were searched to identify genes associated with selected molecules and obesity, as well as genes that overlap obesity target genes with genes related to L. edodes. Additionally, analysis was performed using Enrichr KG to predict the disease targets of L. edodes. Finally, network was constructed between the overlapping genes and bioactive molecules using Rstudio. Further in-vitro studies were carried out using 3T3-L1 cell line. The genes related to the selected compounds and obesity were identified and overlapped. The disease targets of L. edodes was predicted by enrichment analysis and was found to be linked to obesity. Furthermore, the hub gene was found to be fatty acid amide hydrolase, and the key bioactive compound was hexadecanoic acid methyl ester. The in-vitro cell culture studies confirmed the inhibition of adipogenesis in mushroom extract-treated 3T3-L1 cells and the augmentation of adiponectin. The study suggests that the hub gene fatty acid amide hydrolase might alleviate obesity by inhibiting arachidonoyl ethanolamide signaling, which would enhance the action of fatty acid amide hydrolase and limit appetite in L. edodes extract.

In silico investigations and molecular insights for designing tRNA-encoded peptides as potential therapeutics for targeting over-expressed receptors in breast cancer

tRNA- Encoded Peptides (tREPs) have recently been discovered as new functional peptides and hold promise as therapeutics for anti-parasitic applications. In this study, in silico investigations were conducted to design tRNA-encoded peptides with the potential to target over-expressed receptors in breast cancer cells. tRNA genes were translated into corresponding peptides (tREPs) using computational tools. The tREPs, which were predicted as anticancer peptides, were then screened for various ADMET properties. Molecular docking studies were conducted for three cancer target receptors, the Estrogen Receptor (ER), Peroxisome Proliferator-Activated Receptor (PPAR) and the Epidermal Growth Factor Receptor (EGFR). Based on the docking results, specific tREPs were screened and molecular dynamics simulations were performed, and the binding energies were further explored using MMPBSA calculations. The peptide Pep1 (DWIAWRHHNDIVSWLTCGPRFKSWS) and Pep2 (GFIAWWSRHLELAQTRFKSWWS) exhibited a good binding affinity against the Estrogen Receptor (ER) and the Peroxisome Proliferator-Activated Receptor Alpha (PPAR) cancer target. The Pep1-ER and Pep1-PPAR complex maintained an average of two hydrogen bonds throughout the simulation and demonstrated a higher negative binding free energy of -72.27 kcal/mol and -65.16 kcal/mol respectively, as calculated by MMPBSA. Therefore, the tREPs designed as anticancer peptides in this study provide novel approaches for potential anticancer therapeutic modalities.Communicated by Ramaswamy H. Sarma.

A comprehensive review on the antidiabetic attributes of thiazolidine-4-ones: Synthetic strategies and structure-activity relationships

The thiazolidine-4-one scaffold has recently emerged as a potential pharmacophore having clinical significance for medicinal chemists. This heterocyclic ring has been reported to possess a plethora of biological activities, including antidiabetic activity that has inspired researchers to integrate this core with different pharmacophoric fragments to design novel and effective antidiabetic leads. The antidiabetic activity has been observed due to the ability of the thiazolidine-4-one nucleus to interact with different biological targets, including peroxisome proliferator-activated receptor γ, protein tyrosine phosphatase 1B, aldose reductase, α-glucosidase, and α-amylase. The present review discusses the mode of action of thiazolidine-4-ones through these antidiabetic drug targets. This review attempts to summarize and analyze the recent developments with regard to the antidiabetic potential of thiazolidine-4-ones covering different synthetic strategies, structure-activity relationships, and docking studies reported in the literature. The significance of various structural modifications at C-2, N-3, and C-5 of the thiazolidine-4-one ring has also been discussed in this manuscript. This comprehensive compilation will provide an inevitable scope for the design and development of potential antidiabetic drug candidates having a thiazolidine-4-one core.

Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model

Living organisms receive necessary energy substances directly from cellular respiration. The completion of electron storage and transportation requires the process of cellular respiration with the aid of electron transport chains. Therefore, the work of deciphering electron transport proteins is inevitably needed. The identification of these proteins with high performance has a prompt dependence on the choice of methods for feature extraction and machine learning algorithm. In this study, protein sequences served as natural language sentences comprising words. The nominated word embedding-based feature sets, hinged on the word embedding modulation and protein motif frequencies, were useful for feature choosing. Five word embedding types and a variety of conjoint features were examined for such feature selection. The support vector machine algorithm consequentially was employed to perform classification. The performance statistics within the 5-fold cross-validation including average accuracy, specificity, sensitivity, as well as MCC rates surpass 0.95. Such metrics in the independent test are 96.82, 97.16, 95.76 percent, and 0.9, respectively. Compared to state-of-the-art predictors, the proposed method can generate more preferable performance above all metrics indicating the effectiveness of the proposed method in determining electron transport proteins. Furthermore, this study reveals insights about the applicability of various word embeddings for understanding surveyed sequences.

In Silico Studies of Tumor Targeted Peptide-Conjugated Natural Products for Targeting Over-Expressed Receptors in Breast Cancer Cells Using Molecular Docking, Molecular Dynamics and MMGBSA Calculations

In this work, in silico studies were carried out for the design of diterpene and polyphenol-peptide conjugates to potentially target over-expressed breast tumor cell receptors. Four point mutations were induced into the known tumor-targeting peptide sequence YHWYGYTPQN at positions 1, 2, 8 and 10, resulting in four mutated peptides. Each peptide was separately conjugated with either chlorogenate, carnosate, gallate, or rosmarinate given their known anti-tumor activities, creating dual targeting compounds. Molecular docking studies were conducted with the epidermal growth factor receptor (EGFR), to which the original peptide sequence is known to bind, as well as the estrogen receptor (ERα) and peroxisome proliferator-activated receptor (PPARα) using both Autodock Vina and FireDock. Based on docking results, peptide conjugates and peptides were selected and subjected to molecular dynamics simulations. MMGBSA calculations were used to further probe the binding energies. ADME studies revealed that the compounds were not CYP substrates, though most were Pgp substrates. Additionally, most of the peptides and conjugates showed MDCK permeability. Our results indicated that several of the peptide conjugates enhanced binding interactions with the receptors and resulted in stable receptor-ligand complexes; Furthermore, they may successfully target ERα and PPARα in addition to EGFR and may be further explored for synthesis and biological studies for therapeutic applications.

Discovery of novel modulators for the PPARα (peroxisome proliferator activated receptor α): Potential therapies for nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is a severe liver disease causing serious liver complications, including nonalcoholic steatohepatitis (NASH). Nuclear receptor PPARα (peroxisome proliferator-activated receptor α) has drawn special attention recently as a potential developmental drug target to treat type-2 diabetes and related diseases due to its unique functions in regulating lipid metabolism, promoting triglyceride oxidation, and suppressing hepatic inflammation, raising interest in PPARα agonists as potential therapies for NAFLD. However, how PPARα coordinates potential treatment of NAFLD and NASH between various metabolic pathways is still obscure. Here, we show that the DY series of novel selective PPARα modulators activate PPARα by up-regulating PPARα target genes directly involved in NAFLD and NASH. The design, synthesis, docking studies, and in vitro and in vivo evaluation of the novel DY series of PPARα agonists are described.

Molecular Docking and Dynamics Simulation Analysis of Thymoquinone and Thymol Compounds from Nigella sativa L. that Inhibit Cag A and Vac A Oncoprotein of Helicobacter pylori: Probable Treatment of H. pylori Infections

BACKGROUND

Helicobacter pylori infection is accountable for most of the peptic ulcer and intestinal cancers. Due to the uprising resistance towards H. pylori infection through the present and common proton pump inhibitors regimens, the investigation of novel candidates is the inevitable issue. Medicinal plants have always been a source of lead compounds for drug discovery. The research of the related effective enzymes linked with this gram-negative bacterium is critical for the discovery of novel drug targets.

OBJECTIVE

The aim of the study is to identify the best candidate to evaluate the inhibitory effect of thymoquinone and thymol against H. pylori oncoproteins, Cag A and Vac A in comparison to the standard drug, metronidazole by using a computational approach.

MATERIALS AND METHODS

The targeted oncoproteins, Cag A and Vac A were retrieved from RCSB PDB. Lipinski's rule and ADMET toxicity profiling were carried out on the phytoconstituents of the N. sativa. The two compounds of N. sativa were further analyzed by molecular docking and MD simulation studies. The reported phytoconstituents, thymoquinone and thymol present in N. sativa were docked with H. pylori Cag A and Vac A oncoproteins. Structures of ligands were prepared using ChemDraw Ultra 10 software and then changed into their 3D PDB structures using Molinspiration followed by energy minimization by using software Discovery Studio client 2.5.

RESULTS

The docking results revealed the promising inhibitory potential of thymoquinone against Cag A and Vac A with docking energy of -5.81 kcal/mole and -3.61kcal/mole, respectively. On the contrary, the inhibitory potential of thymol against Cag A and Vac A in terms of docking energy was -5.37 kcal/mole and -3.94kcal/mole as compared to the standard drug, metronidazole having docking energy of -4.87 kcal/mole and -3.20 kcal/mole, respectively. Further, molecular dynamic simulations were conducted for 5ns for optimization, flexibility prediction, and determination of folded Cag A and Vac A oncoproteins stability. The Cag A and Vac A oncoproteins-TQ complexes were found to be quite stable with the root mean square deviation value of 0.2nm.

CONCLUSION

The computational approaches suggested that thymoquinone and thymol may play an effective pharmacological role to treat H. pylori infection. Hence, it could be summarized that the ligands thymoquinone and thymol bound and interacted well with the proteins Cag A and Vac A as compared to the ligand MTZ. Our study showed that all lead compounds had good interaction with Cag A and Vac A proteins and suggested them to be a useful target to inhibit H. pylori infection.

Network pharmacology of bioactives from Sorghum bicolor with targets related to diabetes mellitus

BACKGROUND

Sorghum bicolor (SB) is rich in protective phytoconstituents with health benefits and regarded as a promising source of natural anti-diabetic substance. However, its comprehensive bioactive compound(s) and mechanism(s) against type-2 diabetes mellitus (T2DM) have not been exposed. Hence, we implemented network pharmacology to identify its key compounds and mechanism(s) against T2DM.

METHODS

Compounds in SB were explored through GC-MS and screened by Lipinski's rule. Genes associated with the selected compounds or T2DM were extracted from public databases, and the overlapping genes between SB-compound related genes and T2DM target genes were identified using Venn diagram. Then, the networking between selected compounds and overlapping genes was constructed, visualized, and analyzed by RStudio. Finally, affinity between compounds and genes was evaluated via molecular docking.

RESULTS

GC-MS analysis of SB detected a total of 20 compounds which were accepted by the Lipinski's rule. A total number of 16 compounds-related genes and T2DM-related genes (4,763) were identified, and 81 overlapping genes between them were selected. Gene set enrichment analysis exhibited that the mechanisms of SB against T2DM were associated with 12 signaling pathways, and the key mechanism might be to control blood glucose level by activating PPAR signaling pathway. Furthermore, the highest affinities were noted between four main compounds and six genes (FABP3-Propyleneglyco monoleate, FABP4-25-Oxo-27-norcholesterol, NR1H3-Campesterol, PPARA-β-sitosterol, PPARD-β-sitosterol, and PPARG-β-sitosterol).

CONCLUSION

Our study overall suggests that the four key compounds detected in SB might ameliorate T2DM severity by activating the PPAR signaling pathway.

Discovery of new promising USP14 inhibitors: computational evaluation of the thumb-palm pocket

Ubiquitin-specific protease 14 (USP14) is a member of the deubiquitinating enzymes (DUBs) involved in disrupting the ubiquitin-proteasome regulation system, responsible for the degradation of impaired and misfolded proteins, which is an essential mechanism in eukaryotic cells. The involvement of USP14 in cancer progression and neurodegenerative disorders has been reported. Thereof USP14 is a prime therapeutic target; hence, designing efficacious inhibitors against USP14 is central in curbing these conditions. Herein, we relied on structural bioinformatics methods incorporating molecular docking, molecular mechanics generalized born surface area (MM-GBSA), molecular dynamics simulation (MD simulation), and ADME to identify potential allosteric USP14 inhibitors. A library of over 733 compounds from the PubChem repository with >90% match to the IU1 chemical structure was screened in a multi-step framework to attain prospective drug-like inhibitors. Two potential lead compounds (CID 43013232 and CID 112370349) were shown to record better binding affinity compared to IU1, but with subtle difference to IU1-47, a 10-fold potent compound when compared to IU1. The stability of the lead molecules complexed with USP14 was studied via MD simulation. The molecules were found to be stable within the binding site throughout the 50 ns simulation time. Moreover, the protein-ligand interactions across the simulation run time suggest Phe331, Tyr476, and Gln197 as crucial residues for USP14 inhibition. Furthermore, in-silico pharmacological evaluation revealed the lead compounds as pharmacological sound molecules. Overall, the methods deployed in this study revealed two novel candidates that may show selective inhibitory activity against USP14, which could be exploited to produce potent and harmless USP14 inhibitors.Communicated by Ramaswamy H. Sarma.

Scaffold-based selective SHP2 inhibitors design using core hopping, molecular docking, biological evaluation and molecular simulation

PTPN11 (coding the gene of SHP2), a classic non-receptor protein tyrosine phosphatase, is implicated in multiple cell signaling pathway. Abnormal activation of SHP2 has been shown to contribute to a variety of human diseases, including Juvenile myelomonocytic leukemia (JMML), Noonan syndrome and tumors. Thus, the SHP2 inhibitors have important therapeutic value. Here, based on the compound PubChem CID 8,478,960 (IC₅₀ = 45.01 μM), a series of thiophene [2,3-d] pyrimidine derivatives (IC₅₀ = 0.4-37.87 μM) were discovered as novel and efficient inhibitors of SHP2 through powerful "core hopping" and CDOCKER technology. Furthermore, the SHP2-PTP phosphatase activity assay indicated that Comp#5 (IC₅₀ = 0.4 μM) was the most active SHP2 inhibitor. Subsequently, the effects of Comp#5 on the structure and function of SHP2 were investigated through molecular dynamics (MD) simulation and post-kinetic analysis. The result indicated that Comp#5 enhanced the interaction of residues THR357, ARG362, LYS366, PRO424, CYS459, SER460, ALA461, ILE463, ARG465, THR507 and GLN510 with the surrounding residues, improving the stability of the catalytic active region and the entrance of catalytic active region. In particular, the Comp#5 conjugated with residue ARG362, elevating the efficient and selectivity of SHP2 protein. The study here may pave the way for discovering the novel SHP2 inhibitors for suffering cancer patients.

Pimpinella anisum Essential Oil Nanoemulsion Toxicity against Tribolium castaneum? Shedding Light on Its Interactions with Aspartate Aminotransferase and Alanine Aminotransferase by Molecular Docking

The insecticidal activity is the result of a series of complex interactions between toxic substances as ligands and insect’s enzymes as targets. Actually, synthetic insecticides used in pest control programs are harmful to the environment and may affect non-target organisms; thus, the use of natural products as pest control agents can be very attractive. In the present work, the toxic effect of aniseed (Pimpinella anisum L.) essential oil (EO) and its nanoemulsion (NE) against the red flour beetle Tribolium castaneum, has been evaluated. To assess the EO mode of action, the impact of sub-lethal concentrations of aniseed EO and NE was evaluated on enzymatic and macromolecular parameters of the beetles, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), total protein, total lipids and glucose. Finally, a molecular docking study was conducted to predict the mode of action of the major EO and NE components namely E-anethole, Limonene, alpha-himalachalene, trans-Verbenol and Linalool at binding site of the enzymes AST and ALT. Herein, the binding location of the main compounds in both proteins are discussed suggesting the possible interactions between the considered enzymes and ligands. The obtained results open new horizons to understand the evolution and response of insect-plant compounds interactions and their effect predicted at the molecular levels and side effects of both animal and human.

Critical Insight into the Design of PPAR-γ Agonists by Virtual Screening Techniques

BACKGROUND

Design of novel PPAR-γ modulators with better binding efficiency and fewer side effects to treat type 2 diabetes is still a challenge for medicinal chemists. Cost and time efficient computational methods have presently become an integral part of research in nuclear receptors and their ligands, enabling hit to lead identification and lead optimization. This review will focus on cutting-edge technologies used in most recent studies on the design of PPAR- γ agonists and will discuss the chemistry of few molecules which emerged successful.

METHODS

Literature review was carried out in google scholar using customized search from 2011- 2017. Computer-aided design methods presented in this article were used as search terms to retrieve corresponding literature.

RESULTS

Virtual screening of natural product libraries is an effective strategy to harness nature as the source of ligands for PPARs. Rigid and induced fit docking and core hopping approach in docking are rapid screening methods to predict the PPAR- γ and PPAR-α/ γ dual agonistic activity. Onedimensional drug profile matching is one of the recent virtual screening methods by which an antiprotozoal drug, Nitazoxanide was identified as a PPAR- γ agonist.

CONCLUSION

It is concluded that to achieve a convincing and reliable design of PPAR-γ agonist by virtual screening techniques, customized workflow comprising of appropriate models is essential in which methods may be applied either sequentially or simultaneously.

An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule

OBJECTIVE

One of the most challenging and also the most difficult problems is how to formulate a biological sequence with a vector but considerably keep its sequence order information.

METHODS

To address such a problem, the approach of Pseudo Amino Acid Components or PseAAC has been developed.

RESULTS AND CONCLUSION

It has become increasingly clear via the 10-year recollection that the aforementioned proposal has been indeed very powerful.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

BACKGROUND

Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics.

OBJECTIVE

In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed.

RESULTS

Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design.

CONCLUSION

This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule

By reducing amino acid alphabet, the protein complexity can be significantly simplified, which could improve computational efficiency, decrease information redundancy and reduce chance of overfitting. Although some reduced alphabets have been proposed, different classification rules could produce distinctive results for protein sequence analysis. Thus, it is urgent to construct a systematical frame for reduced alphabets. In this work, we constructed a comprehensive web server called RAACBook for protein sequence analysis and machine learning application by integrating reduction alphabets. The web server contains three parts: (i) 74 types of reduced amino acid alphabet were manually extracted to generate 673 reduced amino acid clusters (RAACs) for dealing with unique protein problems. It is easy for users to select desired RAACs from a multilayer browser tool. (ii) An online tool was developed to analyze primary sequence of protein. The tool could produce K-tuple reduced amino acid composition by defining three correlation parameters (K-tuple, g-gap, λ-correlation). The results are visualized as sequence alignment, mergence of RAA composition, feature distribution and logo of reduced sequence. (iii) The machine learning server is provided to train the model of protein classification based on K-tuple RAAC. The optimal model could be selected according to the evaluation indexes (ROC, AUC, MCC, etc.). In conclusion, RAACBook presents a powerful and user-friendly service in protein sequence analysis and computational proteomics. RAACBook can be freely available at http://bioinfor.imu.edu.cn/raacbook.

Database URL: http://bioinfor.imu.edu.cn/raacbook

To Probe Full and Partial Activation of Human Peroxisome Proliferator-Activated Receptors by Pan-Agonist Chiglitazar Using Molecular Dynamics Simulations

Chiglitazar is a promising new-generation insulin sensitizer with low reverse effects for the treatment of type II diabetes mellitus (T2DM) and has shown activity as a nonselective pan-agonist to the human peroxisome proliferator-activated receptors (PPARs) (i.e., full activation of PPARγ and a partial activation of PPARα and PPARβ/δ). Yet, it has no high-resolution complex structure with PPARs and its detailed interactions and activation mechanism remain unclear. In this study, we docked chiglitazar into three experimentally resolved crystal structures of hPPAR subtypes, PPARα, PPARβ/δ, and PPARγ, followed by 3 μs molecular dynamics simulations for each system. Our MM-GBSA binding energy calculation revealed that chiglitazar most favorably bound to hPPARγ (-144.6 kcal/mol), followed by hPPARα (-138.0 kcal/mol) and hPPARβ (-135.9 kcal/mol), and the order is consistent with the experimental data. Through the decomposition of the MM-GBSA binding energy by residue and the use of two-dimensional interaction diagrams, key residues involved in the binding of chiglitazar were identified and characterized for each complex system. Additionally, our detailed dynamics analyses support that the conformation and dynamics of helix 12 play a critical role in determining the activities of the different types of ligands (e.g., full agonist vs. partial agonist). Rather than being bent fully in the direction of the agonist versus antagonist conformation, a partial agonist can adopt a more linear conformation and have a lower degree of flexibility. Our finding may aid in further development of this new generation of medication.

Synthesis, evaluation, molecular dynamics simulation and targets identification of novel pyrazole-containing imide derivatives

A new series of novel pyrazole-containing imide derivatives were synthesized and evaluated for their anticancer activities against A-549, Bel7402, and HCT-8 cell lines. Among these compounds A2, A4, A11 and A14 possessed high inhibition activity against A-549 cell lines with IC₅₀ values at 4.91, 3.22, 27.43 and 18.14 μM, respectively, better than that of 5-fluorouracil (IC₅₀=59.27 μM). A2, A4, and A11 also exhibited significant inhibitory activity towards HCT-8 and Bel7402 cell lines. Interestingly, the Heat Shock Protein 90α (Hsp90α, PDB ID: 1UYK) was found to be the potential drug target of these synthesized compounds with the aid of PharmMapper server (http://lilab.ecust.edu.cn/pharmmapper/) and docking module of Schrödinger (Maestro 10.2). Additionally, molecular dynamics simulation was performed out to explore the most likely binding mode of compound A2 with Hsp90α.Communicated by Ramaswamy H. Sarma.

The Cooperative Effect between Polybasic Region (PBR) and Polysialyltransferase Domain (PSTD) within Tumor-Target Polysialyltranseferase ST8Sia II

ST8Sia II (STX) is a highly homologous mammalian polysialyltransferase (polyST), which is a validated tumor-target in the treatment of cancer metastasis reliant on tumor cell polysialylation. PolyST catalyzes the synthesis of α2,8-polysialic acid (polySia) glycans by carrying out the activated CMP-Neu5Ac (Sia) to N- and O-linked oligosaccharide chains on acceptor glycoproteins. In this review article, we summarized the recent studies about intrinsic correlation of two polybasic domains, Polysialyltransferase domain (PSTD) and Polybasic region (PBR) within ST8Sia II molecule, and suggested that the critical amino acid residues within the PSTD and PBR motifs of ST8Sia II for polysialylation of Neural cell adhesion molecules (NCAM) are related to ST8Sia II activity. In addition, the conformational changes of the PSTD domain due to point mutations in the PBR or PSTD domain verified an intramolecular interaction between the PBR and the PSTD. These findings have been incorporated into Zhou's NCAM polysialylation/cell migration model, which will provide new perspectives on drug research and development related to the tumor-target ST8Sia II.

Progress in the Mechanism and Clinical Application of Cilostazol

Cilostazol is a unique platelet inhibitor that has been used clinically for more than 20 years. As a phosphodiesterase type III inhibitor, cilostazol is capable of reversible inhibition of platelet aggregation and vasodilation, has antiproliferative effects, and is widely used in the treatment of peripheral arterial disease, cerebrovascular disease, percutaneous coronary intervention, etc. This article briefly reviews the pharmacological mechanisms and clinical application of cilostazol.

Cheminformatics in the Identification of Drug Classes for the Treatment of Type 2 Diabetes

Computer-Aided Drug Design has developed into a powerful suite of methods that complement experimental approaches to the identification of new pharmacologically active compounds. In particular, virtual screening has become a standard tool for lead identification. Diverse examples of the application of virtual screening applied to T2DM target proteins have been reported. While several of these indicate successful identification of new lead compounds from synthetic chemical and natural product databases, many of them have been performed on a small scale and with limited validation. Careful study design and collaboration with cheminformaticians and computational chemists will enable these approaches to fulfil their potential for T2DM.

A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration

Polysialic acid (polySia) is a novel glycan that posttranslationally modifies neural cell adhesion molecules (NCAMs) in mammalian cells. Up-regulation of polySia-NCAM expression or NCAM polysialylation is associated with tumor cell migration and progression in many metastatic cancers and neurocognition. It has been known that two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST), can catalyze polysialylation of NCAM, and two polybasic domains, polybasic region (PBR) and polysialyltransferase domain (PSTD) in polySTs play key roles in affecting polyST activity or NCAM polysialylation. However, the molecular mechanisms of NCAM polysialylation and cell migration are still not entirely clear. In this minireview, the recent research results about the intermolecular interactions between the PBR and NCAM, the PSTD and cytidine monophosphate-sialic acid (CMP-Sia), the PSTD and polySia, and as well as the intramolecular interaction between the PBR and the PSTD within the polyST, are summarized. Based on these cooperative interactions, we have built a novel model of NCAM polysialylation and cell migration mechanisms, which may be helpful to design and develop new polysialyltransferase inhibitors.

Current Biochemical Applications and Future Prospects of Chlorotoxin in Cancer Diagnostics and Therapeutics

Chlorotoxin (CTX) is a minute 4 kDa protein made up of 36 amino acid residues, commonly known for its binding affinity to chloride channels and matrix metalloproteinase-2 (MMP-2) of glioma tumors of the spine and brain. This property and the possibility of conjugating this peptide to nanoparticles have enabled its diverse use in various biotechnological and biomedical applications for cancer treatment, such as in tumor imaging and radiotherapy. Because of the fascinating biological properties CTX possesses, elucidating its mechanism of action may hold promise for the development of new and effective therapeutic drugs, as well as more sensitive and highly specific cancer-screening kits. This article therefore reviews the currently known applications of CTX and suggests diverse ways in which it can be applied for the design of improved drugs and diagnostic tools for cancer.

Use of Chou's 5-Steps Rule to Reveal Active Compound and Mechanism of Shuangshen Pingfei San on Idiopathic Pulmonary Fibrosis

BACKGROUND

Shuangshen Pingfei San (SPS) is the derivative from the classic formula Renshen Pingfei San in treating idiopathic pulmonary fibrosis (IPF).

METHODS

In this study, Chou's 5-steps rule was performed to explore the potential active compound and mechanism of SPS on IPF. Compound-target network, target- pathway network, herb-target network and the core gene target interaction network were established and analyzed. A total of 296 compounds and 69 candidate therapeutic targets of SPS in treating IPF were obtained. Network analysis revealed that the main active compounds were flavonoids (such as apigenin, quercetin, naringenin, luteolin), other clusters (such as ginsenoside Rh2, diosgenin, tanshinone IIa), which might also play significant roles. SPS regulated multiple IPF relative genes, which affect fibrosis (PTGS2, KDR, FGFR1, TGFB, VEGFA, MMP2/9) and inflammation (PPARG, TNF, IL13, IL4, IL1B, etc.).

CONCLUSION

In conclusion, anti-pulmonary fibrosis effect of SPS might be related to the regulation of inflammation and pro-fibrotic signaling pathways. These findings revealed that the potential active compounds and mechanisms of SPS on IPF were a benefit to further study.

Investigation of Phospholipase Cγ1 Interaction with SLP76 Using Molecular Modeling Methods for Identifying Novel Inhibitors

The enzyme phospholipase C gamma 1 (PLCγ1) has been identified as a potential drug target of interest for various pathological conditions such as immune disorders, systemic lupus erythematosus, and cancers. Targeting its SH3 domain has been recognized as an efficient pharmacological approach for drug discovery against PLCγ1. Therefore, for the first time, a combination of various biophysical methods has been employed to shed light on the atomistic interactions between PLCγ1 and its known binding partners. Indeed, molecular modeling of PLCγ1 with SLP76 peptide and with previously reported inhibitors (ritonavir, anethole, daunorubicin, diflunisal, and rosiglitazone) facilitated the identification of the common critical residues (Gln805, Arg806, Asp808, Glu809, Asp825, Gly827, and Trp828) as well as the quantification of their interaction through binding energies calculations. These features are in agreement with previous experimental data. Such an in depth biophysical analysis of each complex provides an opportunity to identify new inhibitors through pharmacophore mapping, molecular docking and MD simulations. From such a systematic procedure, a total of seven compounds emerged as promising inhibitors, all characterized by a strong binding with PLCγ1 and a comparable or higher binding affinity to ritonavir (∆G_bind < -25 kcal/mol), one of the most potent inhibitor reported till now.

Physicochemical n-Grams Tool: A tool for protein physicochemical descriptor generation via Chou's 5-step rule

Physicochemical n-Grams Tool (PnGT) is an open-source standalone software for calculating physicochemical descriptors of protein. PnGT was developed using the Python scripting language and developed the user interface using Tkinter. The software currently calculates 33 physicochemical descriptors along with the sequence length for the given protein primary sequence. The descriptor generated by this tool can be directly utilized as the feature vector for the development of proteomics statistical or machine learning predictive model.

Design, synthesis, biological evaluation and molecular dynamics studies of 4-thiazolinone derivatives as protein tyrosine phosphatase 1B (PTP1B) inhibitors

Protein tyrosine phosphatase 1B (PTP1B) is a key negative regulator of insulin signaling pathway, and more and more studies have shown that it is a potential target for the treatment of type 2 diabetes mellitus (T2DM). In this study, 17 new 4-thiazolinone derivatives were designed and synthesized as novel PTP1B inhibitors, and ADMET prediction confirmed that these compounds were to be drug-like. In vitro enzyme activity experiments were performed on these compounds, and it was found that a plurality of compounds had good inhibitory activity and high selectivity against PTP1B protein. Among them, compound 7p exhibited the best inhibitory activity with an IC₅₀ of 0.92 μM. The binding mode of compound 7p and PTP1B protein was explored, revealing the reason for its high efficiency. In addition, molecular dynamics simulations for the PTP1B^WT and PTP1B^comp#7p systems revealed the effects of compound 7p on PTP1B protein at the molecular level. In summary, the study reported for the first time that 4-thiazolinone derivatives as a novel PTP1B inhibitor had good inhibitory activity and selectivity for the treatment of T2DM, providing more options for the development of PTP1B inhibitors. AbbreviationsBBBblood-brain barrierCDC25Bcell division cycle 25 homolog BCYP2D6Cytochrome P450 2D6 bindingDCCMdynamic cross-correlation mapDSDiscovery StudioH bondhydrogen bondHIAhuman intestinal absorptionLARleukocyte antigen-related phosphataseMDmolecular dynamicsMEG-2maternal-effect germ-cell defective 2MM-PBSAmolecular mechanics Poisson Boltzmann surface area)PCAprincipal component analysisPDBProtein Data BankpNPPp-nitrophenyl phosphatePPBplasma protein bindingPTP1Bprotein tyrosine phosphotase 1BRMSDroot mean square deviationRMSFroot mean square fluctuationSHP-1src homologous phosphatase-1SHP-2src homologous phosphatase-2SPCsingle-point chargeTCPTPT cell protein tyrosine phosphataseT2DMType 2 diabetes mellitusVDWvan der WaalsCommunicated by Ramaswamy H. Sarma.

Design, synthesis, biological evaluation and molecular dynamics simulation studies of (R)-5-methylthiazolidin-4-One derivatives as megakaryocyte protein tyrosine phosphatase 2 (PTP-MEG2) inhibitors for the treatment of type 2 diabetes

PTP-MEG2 plays a significant role in insulin production and is able to enhance insulin signaling and improve insulin sensitivity. So, PTP-MEG2 inhibitors are closely associated with type 2 diabetes therapy. A series of novel (R)-5-methylthiazolidin-4-one derivatives were designed and synthesized, and their PTP-MEG2 inhibitory activities (IC₅₀) were determined. Among the desired compounds, 1h shares the highest inhibitory activity (IC₅₀ = 1.34 μM) against PTP-MEG2. Additionally, various post-dynamic analyses confirmed that when compound 1h bound to the PTP-MEG2, the protein conformations became unstable and the function of the pTyr recognition loop (Asn331-Cys338) would be disturbed. And thus, the ideal conformations needed for the catalytic activity was difficult to be maintained. In brief, these might be how the compound 1h worked. Furthermore, we also found that the key residues Arg332 would play a critical role in disturbing the residue interactions. AbbreviationsDCCMdynamic cross-correlation mappingDMFN,N-dimethylformamideDSSPdefinition of secondary structure of proteinsFOXOforkhead transcription factorsMDmolecular dynamicsPCAprincipal component analysisPDBprotein data bankPTKsprotein tyrosine kinasesPTPsprotein tyrosine phosphatasesPTP-MEG2megakaryocyte protein tyrosine phosphatase 2RINresidue interaction networkRINGResidue Interaction Network GeneratorRMSDroot means square deviationRMSFroot mean square fluctuationCommunicated by Ramaswamy H. Sarma.

Advances in Electrochemistry for Monitoring Cellular Chemical Flux

The transport of organic and inorganic molecules, along with inorganic ions across the plasma membrane results in chemical fluxes that reflect the cellular function in healthy and diseased states. Measurement of these chemical fluxes enables the characterization of protein function and transporter stoichiometry, characterization of a single cell and embryo viability prior to implantation, and screening of pharmaceutical agents. Electrochemical sensors emerge as sensitive and non-invasive tools for measuring chemical fluxes immediately outside the cells in the boundary layer, that are capable of monitoring a diverse range of transported analytes including inorganic ions, gases, neurotransmitters, hormones, and pharmaceutical agents. Used on their own or in combination with other methods, these sensors continue to expand our understanding of the function of rare cells and small tissues. Advances in sensor construction and detection strategies continue to improve sensitivity under physiological conditions, diversify analyte detection, and increase throughput. These advances will be discussed in the context of addressing technical challenges to measuring chemical flux in the boundary layer of cells and measuring the resultant changes to the chemical concentration in the bulk media.

In silico minimalist approach to study 2D HP protein folding into an inhomogeneous space mimicking osmolyte effect: First trial in the search of foldameric backbones

We have employed our bioinformatics workbench, named Evolution, a Multi-Agent System based architecture with lattice-bead-models, evolutionary-algorithms, and correlated-networks as inhomogeneous spaces, with different correlation lengths, mimicking osmolyte effect (molecular crowding), to in silico survey protein folding. Resolution is with hydrophobic-polar (H-P) sequences in inhomogeneous 2D square lattices, since general biophysicochemical trends consider i) that the backbone is one of the major components responsible for protein folding and ii) osmolyte effect plays an important role to better folding kinetics and reach deeper optima. We have designed foldamers, as square n × n (n = 3, 4, 5, 6) arrays of hydrophobic cores stabilized by H⋯H contacts, attached through short PP (P₂) or long PPPP (P₄) loops, giving rise to 8 sequences (S₁ to S₈) with known optimal scores. Designed sequences were folded into different inhomogeneous spaces and indeed crowded media induced deeper optima, being crowding necessary to best fold, but the space should be enough constrained to induce folding without banning chain movement. The constrained space plays an important role to reach the optimal structure, depending on designed foldamer sequence size, for an optimal correlation length, implying that media affects the folding pathways as happens in real systems. Designed structures were found, moreover, they undergo to degenerated states, both folding states could survey considering i) backbone information and ii) osmolyte effect. In nature, the proteins fold in different structures aiming to reach a global minimum, but a local minimum could be enough to the protein to be functional or dysfunctional.

2,4-Thiazolidinediones as PTP 1B Inhibitors: A Mini Review (2012-2018)

2,4-thiazolidinedione (TZD) scaffold is a synthetic versatile scaffold explored by medicinal chemists for the discovery of novel molecules for the target-specific approach to treat or manage number of deadly ailments. PTP 1B is the negative regulator of insulin signaling cascade, and its diminished activity results in abolishment of insulin resistance associated with T2DM. The present review focused on the seven years journey (2012-2018) of TZDs as PTP 1B inhibitors with the insight into the amendments in the structural framework of TZD scaffold in order to optimize/design potential PTP 1B inhibitors. We have investigated the synthesized molecules based on TZD scaffold with potential activity profile against PTP 1B. Based on the SAR studies, the combined essential pharmacophoric features of selective and potent TZDs have been mapped and presented herewith for further design and synthesis of novel inhibitors of PTP 1B. Compound 46 bearing TZD scaffold with N-methyl benzoic acid and 5-(3-methoxy-4-phenethoxy) benzylidene exhibited the most potent activity (IC50 1.1 µM). Imidazolidine-2,4-dione, isosteric analogue of TZD, substituted with 1-(2,4-dichlorobenzyl)-5-(3-(2,4- dichlorobenzyloxy)benzylidene) (Compound 15) also endowed with very good PTP inhibitory activity profile (IC50 0.57 µM). It is noteworthy that Z-configuration is essential in structural framework around the double bond of arylidene for the designing of bi-dentate ligands with optimum activity.

Metabolism of Oxalate in Humans: A Potential Role Kynurenine Aminotransferase/Glutamine Transaminase/Cysteine Conjugate Beta-lyase Plays in Hyperoxaluria

Hyperoxaluria, excessive urinary oxalate excretion, is a significant health problem worldwide. Disrupted oxalate metabolism has been implicated in hyperoxaluria and accordingly, an enzymatic disturbance in oxalate biosynthesis can result in the primary hyperoxaluria. Alanine glyoxylate aminotransferase-1 and glyoxylate reductase, the enzymes involving glyoxylate (precursor for oxalate) metabolism, have been related to primary hyperoxalurias. Some studies suggest that other enzymes such as glycolate oxidase and alanine glyoxylate aminotransferase-2 might be associated with primary hyperoxaluria as well, but evidence of a definitive link is not strong between the clinical cases and gene mutations. There are still some idiopathic hyperoxalurias, which require a further study for the etiologies. Some aminotransferases, particularly kynurenine aminotransferases, can convert glyoxylate to glycine. Based on biochemical and structural characteristics, expression level, subcellular localization of some aminotransferases, a number of them appear able to catalyze the transamination of glyoxylate to glycine more efficiently than alanine glyoxylate aminotransferase-1. The aim of this minireview is to explore other undermining causes of primary hyperoxaluria and stimulate research toward achieving a comprehensive understanding of underlying mechanisms leading to the disease. Herein, we reviewed all aminotransferases in the liver for their functions in glyoxylate metabolism. Particularly, kynurenine aminotransferase-I and III were carefully discussed regarding their biochemical and structural characteristics, cellular localization, and enzyme inhibition. Kynurenine aminotransferase-III is, so far, the most efficient putative mitochondrial enzyme to transaminate glyoxylate to glycine in mammalian livers, might be an interesting enzyme to look over in hyperoxaluria etiology of primary hyperoxaluria and should be carefully investigated for its involvement in oxalate metabolism.

Exploring the cause of the inhibitor 4AX attaching to binding site disrupting protein tyrosine phosphatase 4A1 trimerization by molecular dynamic simulation

Ectopic overexpression of protein tyrosine phosphatase of liver regeneration-1 (PTP4A1, also called PRL-1) markedly enhanced hepatocellular carcinoma (HCC) cells migration and invasion. The PTP4A1 trimerization played a vital role in mediating cell proliferation and motility. Biochemical and structural studies have proved that the compound 4AX, a well-known inhibitor for PRL1, directly binds to the PTP4A1 trimer interface and obstructs trimer formation of PTP4A1. However, the molecular basis of the ligand-4AX inhibition on PTP4A1 trimer conformations remains unclear. In this study, the docking analysis and the molecular dynamics simulation (MD simulation) study were performed to investigate how the molecule binding at each interface disrupted the trimer formation. The results suggested that the ligand-4AX attaching to the binding site changed the conformation of A:Q131, A:Q135 in the AC interface, C:R18, C:P96 in the CA interface and B:Q131 in the BA interface, leading to the weak interactions between subunits and thus resulting in the disruption of the PTP4A1 trimerization.

Toward of Safer Phenylbutazone Derivatives by Exploration of Toxicity Mechanism

A drug design for safer phenylbutazone was been explored by reactivity and docking studies involving single electron transfer mechanism, as well as toxicological predictions. Several approaches about its structural properties were performed through quantum chemistry calculations at the B3LYP level of theory, together with the 6-31+G(d,p) basis sets. Molecular orbital and ionization potential were associated to electron donation capacity. The spin densities contribution showed a preferential hydroxylation at the para-positions of phenyl ring when compared to other positions. In addition, on electron abstractions the aromatic hydroxylation has more impact than alkyl hydroxylation. Docking studies indicate that six structures 1, 7, 8 and 13–15 have potential for inhibiting human as well as murine COX-2, due to regions showing similar intermolecular interactions to the observed for the control compounds (indomethacin and refecoxib). Toxicity can be related to aromatic hydroxylation. In accordance to our calculations, the derivatives here proposed are potentially more active as well safer than phenylbutazone and only structures 8 and 13–15 were the most promising. Such results can explain the biological properties of phenylbutazone and support the design of potentially safer candidates.

A Comprehensive In Silico Method to Study the QSTR of the Aconitine Alkaloids for Designing Novel Drugs

A combined in silico method was developed to predict potential protein targets that are involved in cardiotoxicity induced by aconitine alkaloids and to study the quantitative structure⁻toxicity relationship (QSTR) of these compounds. For the prediction research, a Protein-Protein Interaction (PPI) network was built from the extraction of useful information about protein interactions connected with aconitine cardiotoxicity, based on nearly a decade of literature and the STRING database. The software Cytoscape and the PharmMapper server were utilized to screen for essential proteins in the constructed network. The Calcium-Calmodulin-Dependent Protein Kinase II alpha (CAMK2A) and gamma (CAMK2G) were identified as potential targets. To obtain a deeper insight on the relationship between the toxicity and the structure of aconitine alkaloids, the present study utilized QSAR models built in Sybyl software that possess internal robustness and external high predictions. The molecular dynamics simulation carried out here have demonstrated that aconitine alkaloids possess binding stability for the receptor CAMK2G. In conclusion, this comprehensive method will serve as a tool for following a structural modification of the aconitine alkaloids and lead to a better insight into the cardiotoxicity induced by the compounds that have similar structures to its derivatives.

Design, synthesis, and evaluation of novel l-phenylglycine derivatives as potential PPARγ lead compounds

In accordance with the structural characteristics of thiazolidinedione drugs and highly bioactive tyrosine derivatives, we tentatively designed the l-phenylglycine derivatives TM1 and TM2 based on basic principles of drug design and then synthesized them. The in vitro screening of peroxisome proliferator-activated receptor gamma (PPARγ) activated activity, α-glucosidase inhibitory and dipeptidyl peptidase-4 inhibitory activities showed that the novel molecule M5 had efficient PPAR response element (PPRE) activated activity (PPRE relative activity 105.04% at 10 μg·mL^-1 compared with the positive control pioglitazone, with 100% activity). Therefore, M5 was selected as the hit compound from which the TM3 and TM4 series of compounds were further designed and synthesized. Based on the PPRE relative activities of TM3 and TM4, we discovered another new molecule, TM4h, which had the strongest PPRE relative activity (120.42% at 10 μg·mL^-1). In addition, the concentration-dependent activity of the highly active compounds was determined by assaying their half-maximal effective concentration (EC₅₀) values. The molecular physical parameter calculation and the molecular toxicity prediction were used to theoretically evaluate the lead-likeness and safety of the active compounds. In conclusion, we identified a potential PPARγ lead molecule and developed a tangible strategy for antidiabetic drug development.

The discovery of a novel compound with potent antitumor activity: virtual screening, synthesis, biological evaluation and preliminary mechanism study

Farnesyltransferase has been regarded as a promising drug target against cancer as it is critical for membrane association of several signal transduction proteins. In this study, a novel farnesyltransferase inhibitor (IMB-1406) was identified through virtual screening. It exhibits stronger potency (IC₅₀s: 6.92–8.99 μM) than Sunitinib against all of the tested cancer cell lines. Preliminary studies on mechanism reveal that IMB-1406 induces apoptosis in HepG2 cells by arresting the cell cycle at the S phase, altering anti- and pro-apoptotic proteins leading to mitochondrial dysfunction and activation of caspase-3. This anti-tumor effect is most probably related to the inhibition of farnesyltransferase as indicated by molecular docking. Overall, IMB-1406 is a novel lead compound with potent antitumor activity and deserves further structural modifications.

Structural insights of dipeptidyl peptidase-IV inhibitors through molecular dynamics-guided receptor-dependent 4D-QSAR studies

Dipeptidyl peptidase-IV (DPP-IV) inhibitors are promising antidiabetic agents. Currently, several DPP-IV inhibitors have been approved for therapeutic use in diabetes mellitus. Receptor-dependent 4D-QSAR is comparatively a new approach which uses molecular dynamics simulations to generate conformational ensemble profiles of compounds representing a dynamic state of compounds at a target's binding site. This work describes a receptor-dependent 4D-QSAR study on triazolopiperazine derivatives. QSARINS multiple linear regression method was adopted to generate 4D-QSAR models. A model with 9 variables was found to have better predictive accuracy with [Formula: see text], [Formula: see text] (leave-one-out) = 0.592 and [Formula: see text] predicted = 0.597. The location of these 9 variables at the binding site of DPP-IV revealed the importance of the residues Val711, Tyr662, Tyr666, Val202, Asp200 and Thr199 in making critical interactions with DPP-IV inhibitors. The study of these critical interactions revealed the structural features required in DPP-IV inhibitors. Thus, in this study the importance of a halogen substituent on a phenyl ring, the extent of substitution on the triazolopiperazine ring, the presence of an ionizable amino group and the presence of a hydrophobic substituent that can bind deeper in binding pocket of DPP-IV were revealed.